Systemic lupus erythematosus (SLE) has long been characterized by the prototypical expression of type-1 interferon induced genes (IFIGs). However, because of the pleiotropic roles of many IFIGs, how different peripheral blood mononuclear cells (PBMCs) mediate type-1 interferon signaling to cause disease is largely unknown. Here, we propose to use droplet-based RNA-sequencing to study the interferon response of PBMCs from lupus patients and healthy controls. Leveraging naturally occurring ?genetic barcodes?, we will develop a highly innovative multiplexing strategy that significantly increases the throughput, reduces the cost, and limits unwanted technical noise of current droplet-based RNA-sequencing technologies. We will develop computational algorithms for assigning individual cells to the donor of origin and removing unwanted droplets containing multiple cells. We will use the multiplexing strategy to generate a rich dataset (~250K total cells) that enables, for the first time, the unbiased characterization of the effects of interferon-beta on PBMCs without sorting. We will first compare PBMCs from 8 healthy controls, 8 lupus and 8 lupus nephritis patients, to identify cell-type-specific interferon-beta response signatures that is predictive of disease status and severity. These signatures could be used to better monitor lupus progression and treatment response. By profiling PBMCs from 64 genotyped lupus patients, we will then characterize how common genetic variants affect cell-type-specific responses to interferon-beta, including expression parameters (e.g. variance across single cells) impossible to obtain from bulk RNA-sequencing. These results could be compared to genetic variants associated with lupus identified by genome-wide association studies to better understand the molecular pathology of the disease.